{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T20:24:33Z","timestamp":1774556673353,"version":"3.50.1"},"reference-count":63,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2016,1,11]],"date-time":"2016-01-11T00:00:00Z","timestamp":1452470400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The exploitation of new high revisit frequency satellite observations is an important opportunity for agricultural applications. The Sentinel-2 for Agriculture project S2Agri (http:\/\/www.esa-sen2agri.org\/SitePages\/Home.aspx) is designed to develop, demonstrate and facilitate the Sentinel-2 time series contribution to the satellite EO component of agriculture monitoring for many agricultural systems across the globe. In the framework of this project, this article studies the construction of a dynamic cropland mask. This mask consists of a binary \u201cannual-cropland\/no-annual-cropland\u201d map produced several times during the season to serve as a mask for monitoring crop growing conditions over the growing season. The construction of the mask relies on two classical pattern recognition techniques: feature extraction and classification. One pixel- and two object-based strategies are proposed and compared. A set of 12 test sites are used to benchmark the methods and algorithms with regard to the diversity of the agro-ecological context, landscape patterns, agricultural practices and actual satellite observation conditions. The classification results yield promising accuracies of around 90% at the end of the agricultural season. Efforts will be made to transition this research into operational products once Sentinel-2 data become available.<\/jats:p>","DOI":"10.3390\/rs8010055","type":"journal-article","created":{"date-parts":[[2016,1,11]],"date-time":"2016-01-11T10:09:38Z","timestamp":1452506978000},"page":"55","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":122,"title":["Production of a Dynamic Cropland Mask by Processing Remote Sensing Image Series at High Temporal and Spatial Resolutions"],"prefix":"10.3390","volume":"8","author":[{"given":"Silvia","family":"Valero","sequence":"first","affiliation":[{"name":"CESBIO-CNES, CNRS (UMR 5126), IRD, Universit\u00e9 de Toulouse, 31401 Toulouse Cedex 9, France"}]},{"given":"David","family":"Morin","sequence":"additional","affiliation":[{"name":"CESBIO-CNES, CNRS (UMR 5126), IRD, Universit\u00e9 de Toulouse, 31401 Toulouse Cedex 9, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6896-0049","authenticated-orcid":false,"given":"Jordi","family":"Inglada","sequence":"additional","affiliation":[{"name":"CESBIO-CNES, CNRS (UMR 5126), IRD, Universit\u00e9 de Toulouse, 31401 Toulouse Cedex 9, France"}]},{"given":"Guadalupe","family":"Sepulcre","sequence":"additional","affiliation":[{"name":"Earth and Life Institute, Universit\u00e9 Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium"}]},{"given":"Marcela","family":"Arias","sequence":"additional","affiliation":[{"name":"CESBIO-CNES, CNRS (UMR 5126), IRD, Universit\u00e9 de Toulouse, 31401 Toulouse Cedex 9, France"}]},{"given":"Olivier","family":"Hagolle","sequence":"additional","affiliation":[{"name":"CESBIO-CNES, CNRS (UMR 5126), IRD, Universit\u00e9 de Toulouse, 31401 Toulouse Cedex 9, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8383-6465","authenticated-orcid":false,"given":"G\u00e9rard","family":"Dedieu","sequence":"additional","affiliation":[{"name":"CESBIO-CNES, CNRS (UMR 5126), IRD, Universit\u00e9 de Toulouse, 31401 Toulouse Cedex 9, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0012-8410","authenticated-orcid":false,"given":"Sophie","family":"Bontemps","sequence":"additional","affiliation":[{"name":"Earth and Life Institute, Universit\u00e9 Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5355-4988","authenticated-orcid":false,"given":"Pierre","family":"Defourny","sequence":"additional","affiliation":[{"name":"Earth and Life Institute, Universit\u00e9 Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium"}]},{"given":"Benjamin","family":"Koetz","sequence":"additional","affiliation":[{"name":"ESRIN D\/EOP-SEP, European Space Agency, Via Galileo Galilei, 00044 Frascati, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2016,1,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2305","DOI":"10.3390\/rs2092305","article-title":"Global Croplands and their Importance for Water and Food Security in the Twenty-first Century: Towards an Ever Green Revolution that Combines a Second Green Revolution with a Blue Revolution","volume":"2","author":"Thenkabail","year":"2010","journal-title":"Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"647","DOI":"10.14358\/PERS.69.6.647","article-title":"Remote sensing for crop management","volume":"69","author":"Pinter","year":"2003","journal-title":"Photogram. 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